121 research outputs found

    Planning the deployment of fault-tolerant wireless sensor networks

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    Since Wireless Sensor Networks (WSNs) are subject to failures, fault-tolerance becomes an important requirement for many WSN applications. Fault-tolerance can be enabled in different areas of WSN design and operation, including the Medium Access Control (MAC) layer and the initial topology design. To be robust to failures, a MAC protocol must be able to adapt to traffic fluctuations and topology dynamics. We design ER-MAC that can switch from energy-efficient operation in normal monitoring to reliable and fast delivery for emergency monitoring, and vice versa. It also can prioritise high priority packets and guarantee fair packet deliveries from all sensor nodes. Topology design supports fault-tolerance by ensuring that there are alternative acceptable routes to data sinks when failures occur. We provide solutions for four topology planning problems: Additional Relay Placement (ARP), Additional Backup Placement (ABP), Multiple Sink Placement (MSP), and Multiple Sink and Relay Placement (MSRP). Our solutions use a local search technique based on Greedy Randomized Adaptive Search Procedures (GRASP). GRASP-ARP deploys relays for (k,l)-sink-connectivity, where each sensor node must have k vertex-disjoint paths of length ≤ l. To count how many disjoint paths a node has, we propose Counting-Paths. GRASP-ABP deploys fewer relays than GRASP-ARP by focusing only on the most important nodes – those whose failure has the worst effect. To identify such nodes, we define Length-constrained Connectivity and Rerouting Centrality (l-CRC). Greedy-MSP and GRASP-MSP place minimal cost sinks to ensure that each sensor node in the network is double-covered, i.e. has two length-bounded paths to two sinks. Greedy-MSRP and GRASP-MSRP deploy sinks and relays with minimal cost to make the network double-covered and non-critical, i.e. all sensor nodes must have length-bounded alternative paths to sinks when an arbitrary sensor node fails. We then evaluate the fault-tolerance of each topology in data gathering simulations using ER-MAC

    A study into prolonging Wireless Sensor Network lifetime during disaster scenarios

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    A Wireless Sensor Network (WSN) has wide potential for many applications. It can be employed for normal monitoring applications, for example, the monitoring of environmental conditions such as temperature, humidity, light intensity and pressure. A WSN is deployed in an area to sense these environmental conditions and send information about them to a sink. In certain locations, disasters such as forest fires, floods, volcanic eruptions and earth-quakes can happen in the monitoring area. During the disaster, the events being monitored have the potential to destroy the sensing devices; for example, they can be sunk in a flood, burnt in a fire, damaged in harmful chemicals, and burnt in volcano lava etc. There is an opportunity to exploit the energy of these nodes before they are totally destroyed to save the energy of the other nodes in the safe area. This can prolong WSN lifetime during the critical phase. In order to investigate this idea, this research proposes a new routing protocol called Maximise Unsafe Path (MUP) routing using Ipv6 over Low power Wireless Personal Area Networks (6LoWPAN). The routing protocol aims to exploit the energy of the nodes that are going to be destroyed soon due to the environment, by concentrating packets through these nodes. MUP adapts with the environmental conditions. This is achieved by classifying four different levels of threat based on the sensor reading information and neighbour node condition, and represents this as the node health status, which is included as one parameter in the routing decision. High priority is given to a node in an unsafe condition compared to another node in a safer condition. MUP does not allow packet routing through a node that is almost failed in order to avoid packet loss when the node fails. To avoid the energy wastage caused by selecting a route that requires a higher energy cost to deliver a packet to the sink, MUP always forwards packets through a node that has the minimum total path cost. MUP is designed as an extension of RPL, an Internet Engineering Task Force (IETF) standard routing protocol in a WSN, and is implemented in the Contiki Operating System (OS). The performance of MUP is evaluated using simulations and test-bed experiments. The results demonstrate that MUP provides a longer network lifetime during a critical phase of typically about 20\% when compared to RPL, but with a trade-off lower packet delivery ratio and end-to-end delay performances. This network lifetime improvement is crucial for the WSN to operate for as long as possible to detect and monitor the environment during a critical phase in order to save human life, minimise loss of property and save wildlife

    Adaptive mobility: a new policy and research agenda on mobility in horizontal metropolises

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    Data and the city – accessibility and openness. a cybersalon paper on open data

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    This paper showcases examples of bottom–up open data and smart city applications and identifies lessons for future such efforts. Examples include Changify, a neighbourhood-based platform for residents, businesses, and companies; Open Sensors, which provides APIs to help businesses, startups, and individuals develop applications for the Internet of Things; and Cybersalon’s Hackney Treasures. a location-based mobile app that uses Wikipedia entries geolocated in Hackney borough to map notable local residents. Other experiments with sensors and open data by Cybersalon members include Ilze Black and Nanda Khaorapapong's The Breather, a "breathing" balloon that uses high-end, sophisticated sensors to make air quality visible; and James Moulding's AirPublic, which measures pollution levels. Based on Cybersalon's experience to date, getting data to the people is difficult, circuitous, and slow, requiring an intricate process of leadership, public relations, and perseverance. Although there are myriad tools and initiatives, there is no one solution for the actual transfer of that data

    Enabling 5G Edge Native Applications

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